Category: System Biology & Modeling

jagn 1.02 – Java-Based Model for Artificial Gene Networks Generation

jagn 1.02

:: DESCRIPTION

jagn is a software for an Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data, which can be used by computational methods to recover the network topology, and then, analyse the results based on complex networks measurements/topology.

::DEVELOPER

Fabrício Martins Lopes

:: SCREENSHOTS

jagn

:: REQUIREMENTS

  • Linux / Windows / MacOsX
  • Java

:: DOWNLOAD

  jagn

:: MORE INFORMATION

Citation:

Lopes, Fabrício M.; Cesar-Jr, Roberto M.; Costa, Luciano da F.
Gene expression complex networks: synthesis, identification and analysis.
Journal of Computational Biology, v. 18, p. 1353-1367, 2011.

SLML Tools v1.5.2 – Implement Generative Models of Subcellular Location

SLML Tools v1.5.2

:: DESCRIPTION

SLML tools implements the generative models of subcellular location

::DEVELOPER

Murphy Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 SLML Tools

:: MORE INFORMATION

Citation

T. Zhao and R.F. Murphy. (2007)
Automated learning of generative models for subcellular location: Building blocks for systems biology.
Cytometry 71A:978-990.

MyProteinNet 2 – Build Up-to-date PIN for Organisms, Tissues, Cells Subsets and user-defined contexts

MyProteinNet 2

:: DESCRIPTION

The MyProteinNet web server allows users to eas- ily create such context-sensitive protein interaction networks. Users can automatically gather and con- solidate data from up to 11 different databases to create a generic protein interaction network (inter- actome).

::DEVELOPER

Yeger-Lotem Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Basha O, Flom D, Barshir R, Smoly I, Tirman S, Yeger-Lotem E.
MyProteinNet: build up-to-date protein interaction networks for organisms, tissues and user-defined contexts.
Nucleic Acids Res. 2015 Jul 1;43(W1):W258-63. doi: 10.1093/nar/gkv515. Epub 2015 May 18. PMID: 25990735; PMCID: PMC4489290.

MotifNet – Web-server for Network Motif analysis

MotifNet

:: DESCRIPTION

MotifNet allows researchers to analyze integrated networks, where nodes and edges may be labeled, and to search for motifs of up to eight nodes.

::DEVELOPER

Yeger-Lotem Lab

:: SCREENSHOTS

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Smoly IY, Lerman E, Ziv-Ukelson M, Yeger-Lotem E.
MotifNet: a web-server for network motif analysis.
Bioinformatics. 2017 Jun 15;33(12):1907-1909. doi: 10.1093/bioinformatics/btx056. PMID: 28165111.

TissueNet v.2 – Human Tissue Protein-protein Interactions

TissueNet v.2

:: DESCRIPTION

The TissueNet database of human tissue PPIs associates each interaction with human tissues that express both pair mates.

::DEVELOPER

Yeger-Lotem Lab

:: SCREENSHOTS

TissueNet

:: REQUIREMENTS

  • Web Browser 

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Jan;41(Database issue):D841-4. doi: 10.1093/nar/gks1198.
The TissueNet database of human tissue protein-protein interactions.
Barshir R, Basha O, Eluk A, Smoly IY, Lan A, Yeger-Lotem E.

ResponseNet v.3 – Revealing Signaling and Regulatory Networks linking Genetic and Transcriptomic Screening data

ResponseNet v.3

:: DESCRIPTION

ResponseNet is a computational framework that identifies high-probability signaling and regulatory paths that connect input data sets.

::DEVELOPER

Yeger-Lotem Lab

:: SCREENSHOTS

ResponseNet

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W424-9. doi: 10.1093/nar/gkr359.
ResponseNet: revealing signaling and regulatory networks linking genetic and transcriptomic screening data.
Lan A, Smoly IY, Rapaport G, Lindquist S, Fraenkel E, Yeger-Lotem E.

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W198-203. doi: 10.1093/nar/gkt532.
ResponseNet2.0: Revealing signaling and regulatory pathways connecting your proteins and genes–now with human data.
Basha O, Tirman S, Eluk A, Yeger-Lotem E.

iWRAP – Prediction of Cancer-related Protein-protein Interactions

iWRAP

:: DESCRIPTION

iWRAP is a threading program for identifying the putative interface between two protein sequences. iWRAP is based on RAPTOR, which is a single domain threading program. iWRAP considers only the interface of the template to predict interacting residues in a pair of query sequences. iWRAP uses the open-source optimization library (COIN-OR) to minimize the threading energy function.

::DEVELOPER

Raghavendra Hosur (rhosur@mit.edu)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

  iWRAP

:: MORE INFORMATION

Citation

J Mol Biol. 2011 Feb 4;405(5):1295-310. doi: 10.1016/j.jmb.2010.11.025.
iWRAP: An interface threading approach with application to prediction of cancer-related protein-protein interactions.
Hosur R, Xu J, Bienkowska J, Berger B.

DSD 0.5 – Diffusion State Distance Calculation Program

DSD 0.5

:: DESCRIPTION

DSD is a diffusion state distance calculation program. It uses global topological properties of graphs through random walks to compute proximity in terms of node’s funcationality in graphs such as protein-protein interaction networks.

::DEVELOPER

Cowen Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Python

:: DOWNLOAD

 DSD

:: MORE INFORMATION

Citation:

Cao M, Zhang H, Park J, Daniels NM, Crovella ME, Cowen LJ, Hescott B. (2013)
Going the Distance for Protein Function Prediction: A New Distance Metric for Protein Interaction Networks.
PLoS ONE 8(10): e76339. doi:10.1371/journal.pone.0076339 .

BPMs – Validating a particular set of PPI Motifs

BPMs

:: DESCRIPTION

BPMs (Between-pathway models) are network motifs consisting of pairs of putative redundant pathways.

::DEVELOPER

Bioinformatics and Computational Biology Research Group, Tufts University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Python

:: DOWNLOAD

 BPMs

:: MORE INFORMATION

Citation:

J Comput Biol. 2010 Mar;17(3):477-87. doi: 10.1089/cmb.2009.0178.
Evaluating between-pathway models with expression data.
Hescott BJ, Leiserson MD, Cowen LJ, Slonim DK.

Genecentric 1.0.3 – Uncover Graph-theoretic Structure in High-throughput Epistasis data

Genecentric 1.0.3

:: DESCRIPTION

Genecentric is a new package that implements a parallelized version of the Leiserson et al. algorithm (J Comput Biol 18:1399-1409, 2011) for generating generalized BPMs from high-throughput genetic interaction data. Given a matrix of weighted epistasis values for a set of double knock-outs, Genecentric returns a list of generalized BPMs that may represent compensatory pathways.

::DEVELOPER

Bioinformatics and Computational Biology Research Group, Tufts University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsx/WIndows
  • Python

:: DOWNLOAD

 Genecentric

:: MORE INFORMATION

Citation:

Genecentric: a package to uncover graph-theoretic structure in high-throughput epistasis data.
Gallant A, Leiserson MD, Kachalov M, Cowen LJ, Hescott BJ.
BMC Bioinformatics. 2013 Jan 18;14:23. doi: 10.1186/1471-2105-14-23.